https://doi.org/10.5194/hess-2019-217 Preprint. Discussion started: 4 June 2019 c Author(s) 2019. CC BY 4.0 License. 1 Identification of Hotspots of Rainfall Variation 2 Sensitive to Indian Ocean Dipole Mode through 3 Intentional Statistical Simulations 4 5 Jong-Suk Kim1, Phetlamphanh Xaiyaseng1, Lihua Xiong1, Sun-Kwon Yoon2,*, Taesam Lee3,* 6 1 State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan 7 University, Wuhan, 430072, P.R. China;
[email protected] (J.K.);
[email protected] 8 (P.X.);
[email protected] (L.X.) 9 2 Department of Safety and Disaster Prevention Research, Seoul Institute of Technology, Seoul 10 03909, Republic of Korea 11 3 Department of Civil Engineering, ERI, Gyeongsang National University, 501 Jinju-daero, 12 Jinju, Gyeongnam, South Korea, 660-701 13 * Correspondence:
[email protected] (S.Y.);
[email protected] (T.L.) 14 15 Abstract. This study analyzed the sensitivity of rainfall patterns over the Indochina 16 Peninsula (ICP) to sea surface temperature in the Indian Ocean based on statistical 17 simulations of observational data. Quantitative changes in rainfall patterns over the ICP 18 were examined for both wet and dry seasons to identify hotspots sensitive to ocean 19 warming in the Indo-Pacific sector. Rainfall variability across the ICP was confirmed 20 amplified by combined and/or independent effects of the El Niño–Southern Oscillation 21 and the Indian Ocean Dipole (IOD). During the years of El Niño and a positive phase of 22 the IOD, rainfall is less than usual in Thailand, Cambodia, southern Laos, and Vietnam.